Superstable Models for Short-Duration Large-Domain Wave Propagation
This paper introduces a superstable state-space representation suitable for modeling short-duration wave propagation dynamics in large domain. The true system dimensions and the number of output nodes can be extremely large, yet one is only interested in the propagation dynamics during a relatively short time duration. The superstable model can be interpreted as a finite-time version of the standard state-space model that is equivalent to the unit pulse response model. The state-space format of the model allows to user to take advantage of extensive state-space based tools that are widely available for simulation, model reduction, dynamic inversion, Kalman filtering, etc. The practical utility of the new representation is demonstrated in modeling the acoustic propagation of a sound source in a complex city center environment.
KeywordsSound Source System Matrix Model Reduction Superstable Representation Wave Propagation Problem
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- 1.Anderson, T.S., Moran, M.L., Ketcham, S.A., Lacombe, J.: Tracked Vehicle Simulations and Seismic Wavefield Synthesis in Seismic Sensor Systems. Computing in Science and Engineering, 22–28 (2004).Google Scholar
- 2.Ketcham, S.A., Moran, M.L., Lacombe, J., Greenfield, R.J., Anderson, T.S.: Seismic Source Model for Moving Vehicles. IEEE Transactions on Geoscience and Remote Sensing, 43, No. 2, 248–256 (2005).Google Scholar
- 3.Ketcham, S.A., Wilson, D.K., Cudney, H., Parker, M.: Spatial Processing of Urban Acoustic Wave Fields From High-Performance Computations. ISBN: 978–0–7695–3088–5, Digital Object Identifier: 10.1109/HPCMP–UGC.2007.68, DoD High Performance Computing Modernization Program Users Group Conference, 289–295 (2007).Google Scholar
- 5.Ho, B.L., Kalman, R.E.: Effective Construction of Linear State-Variable Models from Input–Output Functions. Proceedings of the 3rd Annual Allerton Confernce on Circuit and System Theory, 152–192 (1965); also Regelungstechnik, 14, 545–548 (1966).Google Scholar
- 6.Juang, J.-N., Cooper, J.E., Wright, J.R.: An Eigensystem Realization Algorithm Using Data Correlations (ERA/DC) for Modal Parameter Identification. Control Theory and Advanced Technology, 4, No. 1, 5–14 (1988).Google Scholar
- 7.Juang, J.-N.: Applied System Identification. Prentice-Hall, Upper Saddle River, NJ (2001).Google Scholar
- 8.Ketcham, S.A., Phan, M.Q., Cudney, H.H.: Reduced-Order Wave-Propagation Modeling Using the Eigensystem Realization Algorithm. The 4th International Conference on High Performance Scientific Computing, Hanoi, Vietnam (2009).Google Scholar